Rakesh Gangadharaiah, H. Su, Elenah B. Rosopa, J. Brooks, Kristin Kolodge, Lisa Boor, Patrick J. Rosopa, Yunyi Jia
The rise of real-time information communication through smartphones and wireless networks enabled the growth of ridesharing services. While personal rideshare services (individuals riding alone or with acquaintances) initially dominated the market, the popularity of pooled ridesharing (individuals sharing rides with people they do not know) has grown globally. However, pooled ridesharing remains less common in the U.S., where personal vehicle usage is still the norm. Vehicle design and rideshare services may need to be tailored to user preferences to increase pooled rideshare adoption. Based on a large, national U.S. survey (N = 5385), the results of exploratory and confirmatory factor analyses suggested that four key factors influence riders’ willingness to consider pooled ridesharing: comfort/ease of use, convenience, vehicle technology/accessibility, and passenger safety. A binomial logistic regression was conducted to determine how the four factors influence one’s willingness to consider pooled ridesharing. The two factors that positively influence riders’ willingness to consider pooled ridesharing are vehicle technology/accessibility (B = 1.10) and convenience (B = 0.94), while lack of passenger safety (B = −0.63) and comfort/ease of use (B = −0.17) are pooled ridesharing deterrents. Understanding user-centered design and service factors are critical to increase the use of pooled ridesharing services in the future.
{"title":"A User-Centered Design Exploration of Factors That Influence the Rideshare Experience","authors":"Rakesh Gangadharaiah, H. Su, Elenah B. Rosopa, J. Brooks, Kristin Kolodge, Lisa Boor, Patrick J. Rosopa, Yunyi Jia","doi":"10.3390/safety9020036","DOIUrl":"https://doi.org/10.3390/safety9020036","url":null,"abstract":"The rise of real-time information communication through smartphones and wireless networks enabled the growth of ridesharing services. While personal rideshare services (individuals riding alone or with acquaintances) initially dominated the market, the popularity of pooled ridesharing (individuals sharing rides with people they do not know) has grown globally. However, pooled ridesharing remains less common in the U.S., where personal vehicle usage is still the norm. Vehicle design and rideshare services may need to be tailored to user preferences to increase pooled rideshare adoption. Based on a large, national U.S. survey (N = 5385), the results of exploratory and confirmatory factor analyses suggested that four key factors influence riders’ willingness to consider pooled ridesharing: comfort/ease of use, convenience, vehicle technology/accessibility, and passenger safety. A binomial logistic regression was conducted to determine how the four factors influence one’s willingness to consider pooled ridesharing. The two factors that positively influence riders’ willingness to consider pooled ridesharing are vehicle technology/accessibility (B = 1.10) and convenience (B = 0.94), while lack of passenger safety (B = −0.63) and comfort/ease of use (B = −0.17) are pooled ridesharing deterrents. Understanding user-centered design and service factors are critical to increase the use of pooled ridesharing services in the future.","PeriodicalId":36827,"journal":{"name":"Safety","volume":" ","pages":""},"PeriodicalIF":1.9,"publicationDate":"2023-05-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"45269111","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Harvy Vivas Pacheco, Diego Rodríguez-Mariaca, Ciro Jaramillo, A. Fandiño-Losada, M. I. Gutiérrez-Martínez
The mobility plan and the road infrastructure works implemented, together with the Bus Rapid Transit (BRT) connected bus system in its first two phases, generated optimistic expectations about the reduction of lethal crashes in the city. This research studies the relationship between investments in transportation infrastructure in the city and the distribution of traffic fatalities. Although it is not strictly speaking an impact assessment, the approach we propose performs geostatistical contrasts between intervened and non-intervened areas, using a geographically weighted model that attempts to model the spatial variability of the factors associated with the intra-urban road traffic crash rate, controlling for infrastructure interventions and some proxy indicators of urban structure. The findings reveal that fatalities decreased in areas both with and without intervention. Despite the expectation of reducing fatal injuries, the differential effects of the interventions were relatively small. The risk of road traffic crashes was even increased in critical points of the city with recurrent lethal crashes. The effects of road interventions on fatal road traffic crashes in Cali did not correspond to the high social and economic costs involved in the BRT system and the work plan.
{"title":"Traffic Fatalities and Urban Infrastructure: A Spatial Variability Study Using Geographically Weighted Poisson Regression Applied in Cali (Colombia)","authors":"Harvy Vivas Pacheco, Diego Rodríguez-Mariaca, Ciro Jaramillo, A. Fandiño-Losada, M. I. Gutiérrez-Martínez","doi":"10.3390/safety9020034","DOIUrl":"https://doi.org/10.3390/safety9020034","url":null,"abstract":"The mobility plan and the road infrastructure works implemented, together with the Bus Rapid Transit (BRT) connected bus system in its first two phases, generated optimistic expectations about the reduction of lethal crashes in the city. This research studies the relationship between investments in transportation infrastructure in the city and the distribution of traffic fatalities. Although it is not strictly speaking an impact assessment, the approach we propose performs geostatistical contrasts between intervened and non-intervened areas, using a geographically weighted model that attempts to model the spatial variability of the factors associated with the intra-urban road traffic crash rate, controlling for infrastructure interventions and some proxy indicators of urban structure. The findings reveal that fatalities decreased in areas both with and without intervention. Despite the expectation of reducing fatal injuries, the differential effects of the interventions were relatively small. The risk of road traffic crashes was even increased in critical points of the city with recurrent lethal crashes. The effects of road interventions on fatal road traffic crashes in Cali did not correspond to the high social and economic costs involved in the BRT system and the work plan.","PeriodicalId":36827,"journal":{"name":"Safety","volume":" ","pages":""},"PeriodicalIF":1.9,"publicationDate":"2023-05-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"45769200","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Natech accidents have an increasing relevance due to the growing number of such events and to their severe consequences. Climate change and global warming are intensifying the occurrence and the magnitude of climate-related natural events, further increasing the risk of cascading sequences triggered by natural disasters impacting industrial installations. The present study focuses on Natech triggered by heat waves. The features of this specific category of Natech events were investigated by past accident analysis, collecting an extended dataset of past events. The dataset analysis allowed the identification of the key factors that characterize these accident scenarios, such as the direct causes, the technological scenario that occurred, the substance categories, and the equipment items more frequently involved. The main direct cause of accidents resulted in an internal pressure increase, exceeding equipment design limits. Fire scenarios represent the most important category of technological scenarios that occurred. Besides equipment items handling liquid and gaseous hydrocarbons, waste storage and processing systems also resulted frequently in accidents, due to the self-decomposition and self-ignition phenomena. The analysis of past accidents also allowed identifying some lessons learned, useful to identify specific actions aimed at preventing and/or mitigating the possible occurrence of these accident scenarios.
{"title":"Natech Accidents Triggered by Heat Waves","authors":"Federica Ricci, Valeria Casson Moreno, V. Cozzani","doi":"10.3390/safety9020033","DOIUrl":"https://doi.org/10.3390/safety9020033","url":null,"abstract":"Natech accidents have an increasing relevance due to the growing number of such events and to their severe consequences. Climate change and global warming are intensifying the occurrence and the magnitude of climate-related natural events, further increasing the risk of cascading sequences triggered by natural disasters impacting industrial installations. The present study focuses on Natech triggered by heat waves. The features of this specific category of Natech events were investigated by past accident analysis, collecting an extended dataset of past events. The dataset analysis allowed the identification of the key factors that characterize these accident scenarios, such as the direct causes, the technological scenario that occurred, the substance categories, and the equipment items more frequently involved. The main direct cause of accidents resulted in an internal pressure increase, exceeding equipment design limits. Fire scenarios represent the most important category of technological scenarios that occurred. Besides equipment items handling liquid and gaseous hydrocarbons, waste storage and processing systems also resulted frequently in accidents, due to the self-decomposition and self-ignition phenomena. The analysis of past accidents also allowed identifying some lessons learned, useful to identify specific actions aimed at preventing and/or mitigating the possible occurrence of these accident scenarios.","PeriodicalId":36827,"journal":{"name":"Safety","volume":" ","pages":""},"PeriodicalIF":1.9,"publicationDate":"2023-05-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"46840659","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
D. Nikolaou, Apostolos Ziakopoulos, Anastasios Dragomanovits, Julia Roussou, G. Yannis
Motorways are typically the safest road environment in terms of injury crashes per million vehicle kilometres; however, given the high severity of crashes occurring therein, there is still space for road safety improvements. The objective of this study is to compare the classification performance of five machine learning techniques for predictions of crash risk levels of motorway segments. To that end, data on crash risk levels, driving behaviour metrics, and road geometry characteristics of 668 motorway segments were exploited. The utilized dataset was divided into training and test subsets, with a proportion of 75% and 25%, respectively. The training subset was used to train the models, whereas the test subset was used for the evaluation of their performance. The response variable of the models was the crash risk level of the considered motorway segments, while the predictors were various road design characteristics and naturalistic driving behaviour metrics. The techniques considered were Logistic Regression, Decision Tree, Random Forest, Support Vector Machine, and K-Nearest Neighbours. Among the five techniques, the Random Forest model achieved the best classification performance (overall accuracy: 89.3%, macro-averaged precision: 89.0%, macro-averaged recall: 88.4%, macro-averaged F1 score: 88.6%). Moreover, the Shapley additive explanations were calculated in order to assist with the interpretation of the model’s outcomes. The findings of this study are particularly useful as the Random Forest model could be used as a highly promising proactive road safety tool for identifying potentially hazardous motorway segments.
{"title":"Comparing Machine Learning Techniques for Predictions of Motorway Segment Crash Risk Level","authors":"D. Nikolaou, Apostolos Ziakopoulos, Anastasios Dragomanovits, Julia Roussou, G. Yannis","doi":"10.3390/safety9020032","DOIUrl":"https://doi.org/10.3390/safety9020032","url":null,"abstract":"Motorways are typically the safest road environment in terms of injury crashes per million vehicle kilometres; however, given the high severity of crashes occurring therein, there is still space for road safety improvements. The objective of this study is to compare the classification performance of five machine learning techniques for predictions of crash risk levels of motorway segments. To that end, data on crash risk levels, driving behaviour metrics, and road geometry characteristics of 668 motorway segments were exploited. The utilized dataset was divided into training and test subsets, with a proportion of 75% and 25%, respectively. The training subset was used to train the models, whereas the test subset was used for the evaluation of their performance. The response variable of the models was the crash risk level of the considered motorway segments, while the predictors were various road design characteristics and naturalistic driving behaviour metrics. The techniques considered were Logistic Regression, Decision Tree, Random Forest, Support Vector Machine, and K-Nearest Neighbours. Among the five techniques, the Random Forest model achieved the best classification performance (overall accuracy: 89.3%, macro-averaged precision: 89.0%, macro-averaged recall: 88.4%, macro-averaged F1 score: 88.6%). Moreover, the Shapley additive explanations were calculated in order to assist with the interpretation of the model’s outcomes. The findings of this study are particularly useful as the Random Forest model could be used as a highly promising proactive road safety tool for identifying potentially hazardous motorway segments.","PeriodicalId":36827,"journal":{"name":"Safety","volume":" ","pages":""},"PeriodicalIF":1.9,"publicationDate":"2023-05-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"45673518","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
This paper presents a conceptual framework with the application of the structural equation modeling (SEM) method for improving safety in the surface mining industry. The focus of the study is to address the essential components of occupational safety and assess them to develop significant linkages because they are often addressed individually. In this study, the risk (accident causation) factors were examined for continuous improvement based on the risk management process and the application of engineering, education, and enforcement. Data collected from mine employees were utilized to evaluate the framework using SEM. The final structure model showed good fit indices, including chi-square to a degree of freedom (x2/df) equal to 2.545, root mean square error of approximation (RMSEA) of 0.034 with a probability of 1.0, and a valid framework path. All the factors had a significant positive effect on workplace conditions and workers’ commitment, except machinery, which had a positive non-significant effect on workplace conditions. The effects of the mediated factors of worker commitment and workplace conditions on the number of accidents were β = −0.76 and β = −0.145, respectively, and the effects on job satisfaction were β = 0.31 and β = 0.433. The research concluded that any risk factor reduction can improve safety in the mining industry; however, the correlation of all factors’ effects magnifies the influence of a single factor. Furthermore, the conceptual framework is recommended for identifying the factors that need modification in order to manage hazards and improve safety in the workplace.
{"title":"Conceptual Framework for Hazards Management in the Surface Mining Industry—Application of Structural Equation Modeling","authors":"S. Sherin, S. Raza, Ishaq Ahmad","doi":"10.3390/safety9020031","DOIUrl":"https://doi.org/10.3390/safety9020031","url":null,"abstract":"This paper presents a conceptual framework with the application of the structural equation modeling (SEM) method for improving safety in the surface mining industry. The focus of the study is to address the essential components of occupational safety and assess them to develop significant linkages because they are often addressed individually. In this study, the risk (accident causation) factors were examined for continuous improvement based on the risk management process and the application of engineering, education, and enforcement. Data collected from mine employees were utilized to evaluate the framework using SEM. The final structure model showed good fit indices, including chi-square to a degree of freedom (x2/df) equal to 2.545, root mean square error of approximation (RMSEA) of 0.034 with a probability of 1.0, and a valid framework path. All the factors had a significant positive effect on workplace conditions and workers’ commitment, except machinery, which had a positive non-significant effect on workplace conditions. The effects of the mediated factors of worker commitment and workplace conditions on the number of accidents were β = −0.76 and β = −0.145, respectively, and the effects on job satisfaction were β = 0.31 and β = 0.433. The research concluded that any risk factor reduction can improve safety in the mining industry; however, the correlation of all factors’ effects magnifies the influence of a single factor. Furthermore, the conceptual framework is recommended for identifying the factors that need modification in order to manage hazards and improve safety in the workplace.","PeriodicalId":36827,"journal":{"name":"Safety","volume":" ","pages":""},"PeriodicalIF":1.9,"publicationDate":"2023-05-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"48142913","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
S. Klauer, Yubin Hong, M. Mollenhauer, J. P. T. Vilela
This study assessed the limitations of the EasyMile EZ10 Gen 3 low-speed automated vehicle (LSAV) while operating on public roadways. The primary interest was to evaluate the infrastructure elements that posed the greatest challenges for the LSAV. A route was chosen that would satisfy a legitimate transit need. This route included more operational complexity and higher traffic volumes than a typical EasyMile LSAV deployment. The results indicate that the LSAV operated at a lower-than-expected speed (6 to 8 mph), with a high frequency of disengagements, and a regular need for safety operator intervention. Four-way stop-sign controlled intersections, three-lane roads with a shared turning lane in the middle, open areas, and areas without clear markings were the most challenging for the LSAV. Some important considerations include the need to have LSAVs operate on roadways where other vehicles may pass more safely, or on streets with slower posted speed limits. Additionally, the low passenger capacity and inability to understand where passengers are located onboard make it hard for the LSAV to replace bus transits. Currently, the LSAV is best suited to provide first/last-mile services, short routes within a controlled access area, and fill in gaps in conventional transits.
{"title":"Infrastructure-Based Performance Evaluation for Low-Speed Automated Vehicle (LSAV)","authors":"S. Klauer, Yubin Hong, M. Mollenhauer, J. P. T. Vilela","doi":"10.3390/safety9020030","DOIUrl":"https://doi.org/10.3390/safety9020030","url":null,"abstract":"This study assessed the limitations of the EasyMile EZ10 Gen 3 low-speed automated vehicle (LSAV) while operating on public roadways. The primary interest was to evaluate the infrastructure elements that posed the greatest challenges for the LSAV. A route was chosen that would satisfy a legitimate transit need. This route included more operational complexity and higher traffic volumes than a typical EasyMile LSAV deployment. The results indicate that the LSAV operated at a lower-than-expected speed (6 to 8 mph), with a high frequency of disengagements, and a regular need for safety operator intervention. Four-way stop-sign controlled intersections, three-lane roads with a shared turning lane in the middle, open areas, and areas without clear markings were the most challenging for the LSAV. Some important considerations include the need to have LSAVs operate on roadways where other vehicles may pass more safely, or on streets with slower posted speed limits. Additionally, the low passenger capacity and inability to understand where passengers are located onboard make it hard for the LSAV to replace bus transits. Currently, the LSAV is best suited to provide first/last-mile services, short routes within a controlled access area, and fill in gaps in conventional transits.","PeriodicalId":36827,"journal":{"name":"Safety","volume":" ","pages":""},"PeriodicalIF":1.9,"publicationDate":"2023-05-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"41585273","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
R. Seva, Imanuel Luir del del Rosario, Lorenzo Miguel Peñafiel, John Michael Young, E. Sybingco
The movement of a motorcycle is one of the critical factors that influences the stability of the ride. It has been established that the gait patterns of drunk and sober people are distinct. However, drunk motorcycle (MC) drivers’ balance has not been investigated as a predictor of intoxication. This paper characterized and used MC and head movements, such as pitch and roll, to predict intoxication while riding. Two separate experiments were conducted to monitor MC and head movement. Male participants were recruited between the ages of 23 and 50 to participate in the study. Participants used alcohol intoxication goggles (AIG) to simulate blood alcohol content (BAC) while driving on a straight path. Placebo goggles were used for control. Results showed that pitch and roll amplitudes of the MC could distinguish drivers wearing placebo and AIGs, as well as the pitch and roll frequency of the head. Deep learning can be used to predict the intoxication of MC riders. The predictive accuracy of the algorithm shows a viable opportunity for the use of movement to monitor drunk riders on the road.
{"title":"Predicting Intoxication Using Motorcycle and Head Movements of Riders Wearing Alcohol Intoxication Goggles","authors":"R. Seva, Imanuel Luir del del Rosario, Lorenzo Miguel Peñafiel, John Michael Young, E. Sybingco","doi":"10.3390/safety9020029","DOIUrl":"https://doi.org/10.3390/safety9020029","url":null,"abstract":"The movement of a motorcycle is one of the critical factors that influences the stability of the ride. It has been established that the gait patterns of drunk and sober people are distinct. However, drunk motorcycle (MC) drivers’ balance has not been investigated as a predictor of intoxication. This paper characterized and used MC and head movements, such as pitch and roll, to predict intoxication while riding. Two separate experiments were conducted to monitor MC and head movement. Male participants were recruited between the ages of 23 and 50 to participate in the study. Participants used alcohol intoxication goggles (AIG) to simulate blood alcohol content (BAC) while driving on a straight path. Placebo goggles were used for control. Results showed that pitch and roll amplitudes of the MC could distinguish drivers wearing placebo and AIGs, as well as the pitch and roll frequency of the head. Deep learning can be used to predict the intoxication of MC riders. The predictive accuracy of the algorithm shows a viable opportunity for the use of movement to monitor drunk riders on the road.","PeriodicalId":36827,"journal":{"name":"Safety","volume":" ","pages":""},"PeriodicalIF":1.9,"publicationDate":"2023-04-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"42794295","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Michael Dyer, S. Gorucu, R. Bock, Roderick Thomas, Jude Liu, Linda Fetzer
All new grain bins produced after 2018 are recommended to have anchor points capable of handling a 2000 lb loading for attachment of bin entry lifeline systems. This study aims to assess the feasibility of a safe entry anchor point retrofit by using finite element analysis (FEA). We used a grain bin owned by Penn State for 3D FEA modeling in SolidWorks. To validate the model results from the FEA model, first strain and then deflection measurements were conducted on the grain. Strain gauges were applied to the grain bin in five locations and strain values were obtained after applying static loads. The strain gauge measurements from the experimental study were compared to the strain output from the FEA simulation. The error seen was far greater than was expected. The most pertinent error source was strain gauge installation error and equipment failure. Then, the vertical roof deflection of the bin was measured using a precision phase-comparison laser while applying incremental static loads to the retrofitted rescue anchor points. The FEA model results were compared to the experimentally measured deflection results. A 3D FEA model of a grain bin was created. A high amount of error was observed in deflections between the measured and FEA modeling. The errors have resulted from the assumptions made during the model creation. However, the SolidWorks Simulation model still may be used to estimate loading scenarios in a safe and non-destructive way. Based on the research findings, the project team recommends that the suitability of any bin to safely accommodate a lifeline and anchor point system must be verified on a case-by-case basis. Evaluation by a professional structural engineer and consulting with the manufacturer are recommended. This recommendation extends to all-grain bins, including those post-2018.
{"title":"Case Study: Modeling a Grain Bin for Safe Entry Retrofit","authors":"Michael Dyer, S. Gorucu, R. Bock, Roderick Thomas, Jude Liu, Linda Fetzer","doi":"10.3390/safety9020028","DOIUrl":"https://doi.org/10.3390/safety9020028","url":null,"abstract":"All new grain bins produced after 2018 are recommended to have anchor points capable of handling a 2000 lb loading for attachment of bin entry lifeline systems. This study aims to assess the feasibility of a safe entry anchor point retrofit by using finite element analysis (FEA). We used a grain bin owned by Penn State for 3D FEA modeling in SolidWorks. To validate the model results from the FEA model, first strain and then deflection measurements were conducted on the grain. Strain gauges were applied to the grain bin in five locations and strain values were obtained after applying static loads. The strain gauge measurements from the experimental study were compared to the strain output from the FEA simulation. The error seen was far greater than was expected. The most pertinent error source was strain gauge installation error and equipment failure. Then, the vertical roof deflection of the bin was measured using a precision phase-comparison laser while applying incremental static loads to the retrofitted rescue anchor points. The FEA model results were compared to the experimentally measured deflection results. A 3D FEA model of a grain bin was created. A high amount of error was observed in deflections between the measured and FEA modeling. The errors have resulted from the assumptions made during the model creation. However, the SolidWorks Simulation model still may be used to estimate loading scenarios in a safe and non-destructive way. Based on the research findings, the project team recommends that the suitability of any bin to safely accommodate a lifeline and anchor point system must be verified on a case-by-case basis. Evaluation by a professional structural engineer and consulting with the manufacturer are recommended. This recommendation extends to all-grain bins, including those post-2018.","PeriodicalId":36827,"journal":{"name":"Safety","volume":" ","pages":""},"PeriodicalIF":1.9,"publicationDate":"2023-04-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"48703610","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Guido Alfaro Degan, Andrea Antonucci, Dario Lippiello
The ISO Standard 10819:2013 defines the method for evaluating the performances of antivibration (AV) gloves, but when used in real fields, the protection can be dissimilar to that labeled. This paper investigates the transmissibility, at the palm level, of three different types of AV gloves (air, gel, neoprene) and an ordinary leather glove, during the use of four similar electric hammers (average weight of 10 kg, and average impact energy of 18 J), in a limestone quarry plant. As the average triaxial transmissibility for all the hammers, results show very limited benefits in reducing the vibration (6%), with no significative differences among the different gloves. The working leather glove, instead, shows a transmissibility quite equal to the unit. Anyway, results can be different for the same glove when used among the different hammers, providing in some cases 19% of protection. Some differences can be found regarding the transmissibility through the three main axes for the same type of glove: the glove in gel seems to perform better in shear than in compression. The transmissibility in compression is around 20% higher than that provided by the manufacturers of the certified gloves. The usage of specific excitation curves during laboratory tests could help in providing a more accurate estimation of the transmissibility of the gloves when used with a specific tool.
{"title":"Efficacy of Antivibration Gloves When Used with Electric Hammers of about 10 kg for Chiseling Limestone Rocks","authors":"Guido Alfaro Degan, Andrea Antonucci, Dario Lippiello","doi":"10.3390/safety9020027","DOIUrl":"https://doi.org/10.3390/safety9020027","url":null,"abstract":"The ISO Standard 10819:2013 defines the method for evaluating the performances of antivibration (AV) gloves, but when used in real fields, the protection can be dissimilar to that labeled. This paper investigates the transmissibility, at the palm level, of three different types of AV gloves (air, gel, neoprene) and an ordinary leather glove, during the use of four similar electric hammers (average weight of 10 kg, and average impact energy of 18 J), in a limestone quarry plant. As the average triaxial transmissibility for all the hammers, results show very limited benefits in reducing the vibration (6%), with no significative differences among the different gloves. The working leather glove, instead, shows a transmissibility quite equal to the unit. Anyway, results can be different for the same glove when used among the different hammers, providing in some cases 19% of protection. Some differences can be found regarding the transmissibility through the three main axes for the same type of glove: the glove in gel seems to perform better in shear than in compression. The transmissibility in compression is around 20% higher than that provided by the manufacturers of the certified gloves. The usage of specific excitation curves during laboratory tests could help in providing a more accurate estimation of the transmissibility of the gloves when used with a specific tool.","PeriodicalId":36827,"journal":{"name":"Safety","volume":" ","pages":""},"PeriodicalIF":1.9,"publicationDate":"2023-04-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"47709071","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
D. Adjekum, N. Y. Owusu-Amponsah, S. Afari, Z. Waller, V. Rasouli, Gary Ullrich, Paul Snyder, Neal Corbin
To fill a gap in understanding of the Generative Voluntary Safety Reporting Culture (GVSRC) in the Gulf of Mexico (GOM) Oil and Gas (O&G) sector, perspectives of stakeholders based on their experiences were explored using attributes of a proposed Offshore Safety Action Program (OSAP) modeled after the Aviation Safety Action Program (ASAP). A phenomenological approach encompassing semi-structured interviews (n = 18) and five focus-group sessions (n = 18) was used to collect data from a cross-section of top management, supervisors, regulatory representatives, and subject-matter experts (SME). Four themes emerged from a Thematic Analysis: (1) Voluntary safety reporting culture, (2) Voluntary safety reporting bottlenecks, (3) Universality, and (4) Organizational review of safety events. Most respondents strongly supported the OSAP because it ensures a formalized adjudication of voluntary safety reports by an Event Review Committee (ERC) with representation from employees, management, and regulators. Most respondents supported the non-punitive and confidential attributes of the OSAP as a means to enhance GVSRC. However, there were varying perspectives on defining intentional disregard for safety under the OSAP. Due to the enumerated challenges of cost, respondents agreed that organizations use a scalable process commensurate with the complexity of their operations when adopting the OSAP. A veritable framework for data-driven corrective actions, organizational learning, and enhanced GVSRC in the offshore sector is a potential policy implication of adopting the OSAP.
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